Cloud computing is heavily promoted as the low-cost alternative to in-house data centers. Yet this is not true for any context and any application. A recent paper with the title “To Move or Not to Move: The Economics of Cloud Computing” by Byung Chul Tak, Bhuvan Urgaonkar, and Anand Sivasubramainam states that especially applications with larger workloads are more expensive to run on the cloud than in a well-managed in-house data center. The researchers from the Pennsylvania State University ran a battery of simulations, applying the TPC-W and TPC-E benchmarks, which emulate e.g. the workload in an online book store or and online brokerage firm.

Doing their simulations over a 10 year time period, the researchers concluded that e.g. small workloads (20 transactions per second) in their example would cost USD 10.000 to run in-house and USD 1.000 to run in the cloud per year. For bigger work loads this cost advantage can turn into the opposite – an in-house implementation costing USD 400.000 a year can easily surpass the USD 1 million a year level in the cloud.

“Overall, we find that in-house provisioning is cost-effective for medium to large workloads, whereas cloud-based options suit small workloads,” the researchers state in the paper. This is yet another hint that the cloud is not necessarily a low-cost alternative for every need and should make decision makers aware to carefully analyze their own situation before making high impact decisions.

2 Responses to “Cloud economics penalizes large workloads”

For these medium to large work loads, a more practical and cost effective use of cloud is for ‘cloud bursting’.

Where there are sudden peaks in demand, if you can bring online cloud based services / infrastructure that integrate seamlessly into your own infrastructure you can increase processing bandwidth at very competitive rates when compared to the purchase, support & maintenance of systems sitting idle the majority of the time in your own data centers.